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Toward Responsive Visualization Services for Scatter/Gather Browsing

机译：面向响应式可视化服务的散布/聚集浏览

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摘要

As a type of relevance feedback, Scatter/Gather demonstrates an interactive approach to relevancernmapping and reinforcement. The Scatter/Gather model, proposed by Cutting, Karger, Pedersen,rnand Tukey (1992), is well known for its effectiveness in situations where it is difficult to preciselyrnspecify a query. However, online clustering on a large data corpus is computationally complex andrnextremely time consuming. This has prohibited the method's real world application for responsivernservices. In this paper, we proposed and evaluated a new clustering algorithm called LAIR2, whichrnhas linear worst-case time complexity and constant running time average for Scatter/Gatherrnbrowsing. Our experiment showed when running on a single processor, the LAIR2 online clusteringrnalgorithm is several hundred times faster than a classic parallel algorithm running on multiplernprocessors. The efficiency of the LAIR2 algorithm promises real-time Scatter/Gather browsingrnservices. We have implemented an online visualization prototype, namely, LAIR2 Scatter/Gatherrnbrowser, to demonstrate its utility and usability.
机译：作为一种相关性反馈，Scatter / Gather演示了一种用于相关性映射和增强的交互式方法。由Cutting，Karger，Pedersen，rnand Tukey（1992）提出的Scatter / Gather模型以其在难以精确指定查询的情况下的有效性而闻名。然而，在大型数据语料库上的在线聚类在计算上非常复杂并且非常耗时。这已经禁止了该方法在响应服务中的实际应用。在本文中，我们提出并评估了一种称为LAIR2的新聚类算法，该算法具有线性最坏情况下的时间复杂度和恒定的运行时间平均值，以实现分散/聚集浏览。我们的实验表明，在单个处理器上运行时，LAIR2在线聚类算法比在多个处理器上运行的经典并行算法快数百倍。 LAIR2算法的效率保证了实时的分散/聚集浏览服务。我们已经实现了一个在线可视化原型，即LAIR2 Scatter / Gatherrnbrowser，以演示其实用性和可用性。

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  • 来源
  • 会议地点 Columbus OH(US);Columbus OH(US)
  • 作者

    Weimao Ke; Javed Mostafa; Yong Liu;

  • 作者单位

    Laboratory of Applied Informatics Research University of North Carolina at Chapel Hill, 216 Lenoir Drive CB#3360, 100 Manning Hall, Chapel Hill,rnNC 27599-3360, U.S.A. Tel: 919- 962-8366, wke@unc.edu;

    rnLaboratory of Applied Informatics Research University of North Carolina at Chapel Hill, 216 Lenoir Drive CB#3360, 100 Manning Hall, Chapel Hill,rnNC 27599-3360, U.S.A. Tel: 919- 962-8366, jm@unc.edu;

    rnLaboratory of Applied Informatics Research University of North Carolina at Chapel Hill, 216 Lenoir Drive CB#3360, 100 Manning Hall, Chapel Hill,rnNC 27599-3360, U.S.A. Tel: 919- 962-8366, yonliu@indiana.edu;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 信息与知识传播;
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